Pharmacogenetics of response to antiresorptive therapy: Vitamin D receptor gene

Tuan V. Nguyen, Associate ProfessorJohn A. Eisman, Professor and Director

Bone and Mineral Research ProgramGarvan Institute of Medical Research

Sydney, Australia

Variability in BMD = 0.12 x MeanVariability in BMD = 3 x Mean

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Nguyen et al, JBMR 1999Average rate of BMD loss: -0.6 1.8 %/yr

Percent change in lumbar spine BMD

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Adapted from Cummings et al, JAMA 1998

Variability in response to therapy: 1-3 x Mean BMD

Osteoporosis heterogenous pathophysiological mechanisms and response to therapy

Individual vs average

Clinical – efficacy and tolerance– Duration– new pharmacologic targets

Theoretical – genetics of BMD– genetics of BMD change– environmental factors

Available data genetic polymorphisms and response to antiresorptive therapy

Genetics of BMD and body composition

rMZ rDZ H2 (%)

Lumar spine BMD 0.74 (0.06) 0.48 (0.10) 77.8

Femoral neck BMD 0.73 (0.06) 0.47 (0.11) 76.4

Total body BMD 0.80 (0.05) 0.48 (0.10) 78.6

Lean mass 0.72 (0.06) 0.32 (0.12) 83.5

Fat mass 0.62 (0.08) 0.30 (0.12) 64.8

Nguyen, et al, Am J Epidemiol 1998

VDR genotype and BMD

• VDR genotype and osteocalcin levels (PNAS, 1992)• VDR genotype and BMD (Nature, 1994)

• Contentious association

• Meta-analysis: 15 cross-sectional, cohort studies

• Bayesian modelling

VDR genotype and lumbar spine BMD

Effect size (bb vs Bb)

-1.0 -0.5 0.0 0.5 1.0 1.5

Melhus H et al.

Kroger H et al.

Riggs BL et al.

Berg JP et al.

Boschictsch et al.

Garneo P et al.

Jorgensen HL et al.

Kiel et al.

McClure L et al.

Vandevyver C et al.

Gennari L et al.

Hansen TS et al.

Gornez C et al.

Langdahl BL et al.

Marc J et al.

Overall

Effect size (bb vs BB)

-2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0

Melhus H et al.

Kroger H et al.

Riggs BL et al.

Berg JP et al.

Boschictsch et al.

Garneo P et al.

Jorgensen HL et al.

Kiel et al.

McClure L et al.

Vandevyver C et al.

Gennari L et al.

Hansen TS et al.

Gornez C et al.

Langdahl BL et al.

Marc J et al.

Overall

Pooled effects of VDR genotype on BMD: Bayesian analysis

Overall difference: 14.7 (95% CI: 0.8 to 42.3) mg/cm2 Overall difference: 5.8 (95% CI: -6.5 to 18.0) mg/cm2

Absolute difference in lumbar spine BMD between bb and BB (g/cm2)

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Absolute difference in lumbar spine BMD between bb and Bb (g/cm2)

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bb - Bb

BsmI b allele associated with higher BMD

Model of drug response

Drug response

Adverse reaction

Drug effect

Activity of other biological systems

Target responsiveness

Drug concentration at target

Drug concentration at other biological systems

Responsiveness at other biological systems

Other predisposition

Adapted from Meisel, et al. J Mol Med 2003

Heritability of BMD change• 21 MZ and 19 DZ twin pairs over 3 years • Changes in lumbar spine BMD:

rMZ = 0.93 vs rDZ = 0.51(Kelly et al. JBMR 1993; 8:11-7)

• 25 MZ and 21 DZ male twin pairs over 14 years• Changes in distal radius BMD:

rMZ=0.61, rDZ=0.41 (NS)(Christian, et al. 1989)

VDR genotype and BMD change

Significant association No significant associationRapuri, J Steroid Biochem & Mol Biol 2004

Gomez, Osteoporosis Int 1999

Guardiola, Ann Int Med 1999

Gough, J Rheumatol 1998

Deng, Hum Genet 1998

Zmuda, JBMR 1997

Ferrari, Lancet 1995

Krall, JBMR 1995

Gunnes, JCEM 1997

Garnero, JBMR 1996

Hansen, Bone 1998

Publication bias?

In “positive” studies, BsmI b allele associated with lesser loss or greater increase in BMD

Inter-subject variability in response to antiresorptive therapy

Percent change in lumbar spine BMD

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Adapted from Cummings et al, JAMA 1998Placebo: n=2218, mean change in LSBMD: 1.5 ± 8.1 %Alendronate: n=2214, mean change in LSBMD: 8.3 ± 7.8 %

Pharmacogenetics of response to antiresorptive treatments

• Few studies

• Candidate gene approach

VDR genotypes and response to Raloxifene Rx

n=66 osteoporotic women; duration of Rx: 1 yr

Palomba et al. Human Reprod 2003; 18:192-8

BMD Bone turnover markers

VDR genotypes and response to Alendronate Rx

n=68 osteoporotic women; duration of Rx: 1 yrPalomba et al. Clin Endocrinol 2003; 58:365-71

BMD

Bone turnover markers

VDR genotype and BMD response to treatment

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ALN RLX ALN+RLX

Adapted from Palomba et al. Clin Endocrinol 2003; Hum Reprod 2003; and Palomba et al, OI 2005 (Epub).

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• Response to antiresorptive therapy is multifactorial (VDR genotypes explained 5-10% of the variability)

Genetic factors and response to antiresorptive therapy

• SNPs profile could allow individualization of treatment

• Issues of study design and interpretation Bayesian decision approach

SNP association studies: Bayesian approach to decision

Alternatives

1. Abandon study

2. Continue data collection

3. Evidence strong enough for molecular exploration

Rationale for decision

True positive assoc. / False positive assoc. = 20/1

(NOT the same as p-value)

A hypothetical scenario

• 20 SNPs (out of 1000 SNPs) are actually associated with BMD response to Rx

• Study power = 80% (i.e., type II error = 20%)

• Type I error = 5%

• Finding: Significant association for 1 SNP (P = 0.05)

• What is the probability that there is indeed an association?

20 SNPs involved; Power = 80%; False +ve = 5%

1000 SNPs

Association (n=20) No association (n=980)

Significant

N=16

Non-significant

Significant

(n=49)

Non-significant

True positive / False positive = 16/49P(True association | Significant result) = 16/(16+49) = 25%

=5%power=80%

The need for lower P-value

About 25% of all findings with “p<0.05” should, if viewed in a scientifically agnostic light, properly be regarded as nothing more than chance findings (1).

• Proportion of significant associations depends on: – p-value, – overall proportion of hypotheses being tested are true– statistical power

• For a ratio (true +ve) / (false +ve) association = 20:1, p-value should be lowered by 400 times

• For a ratio (true +ve) / (false +ve) association = 50:1, p-value should be lowered by 1000 times

(1) J Berger (1987); R Matthews (2001)

Bayesian resolution of conflicting findingChange in LSBMD in response to ALN Rx: bb vs BB genotypes

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Palomba 2003, 2005

P(bb-BB>3%) = 0.91

Marc OI 1999

P(bb-BB>3%) = 0.01

P(bb-BB>3%) = 0.73

Genetic markers could allow identification of those more or less likely to– fracture– respond to a specific treatment– suffer side effects from a specific treatment

With cost-benefits in relation to intervention, Bayesian method offers a powerful approach to individualise inference

Acknowledgments

Nguyen D. Nguyen

Garvan Institute of Medical Research

Regia Congressi Organizing C’tee

Reserved slides

Misunderstanding of P-value

Bisphosphonate treatment was associated with a 5% increase in BMD compared to placebo (p<0.05)

1. It has been proved that bisphosphonate is better than placebo?

2. If the treatment has no effect, there is less than a 5% chance of obtaining such result

3. The observed effect is so large that there is less than 5% chance that the treatment is no better than placebo

4. I don’t know

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1. Better treatment; 2. <5% chance of getting the result if there is no effect; 3. <5% due

to chance 4. I don’t know (Source: Wulffet al., Stat Med 1987; 6:3-10)

P value is NOT• the likelihood that findings are due to chance

• the probability that the null hypothesis is true given the data

• P-value is 0.05, so there is 95% chance that a real difference exists

• With low p-value (p < 0.001) the finding must be true

• The lower p-value, the stronger the evidence for an effect

P-value

• Grew out of quality control during WWII

• Question: the true frequency of bad bullets is 1%, what is the chance of finding 4 or more bad bullets if we test 100 bullets?

• Answer: With some maths (binomial theorem), p=2%

So, So, p-value is the probability of getting p-value is the probability of getting a result as extreme (or more extreme) a result as extreme (or more extreme) than the observed value given an than the observed value given an hypothesishypothesis

Process of ReasoningThe current process of hypothesis testing is a “proof by

contradiction”

If the null hypothesis is true, then the observations are unlikely.

The observations occurred______________________________________

Therefore, the null hypothesis is unlikely

If Tuan has hypertension, then he is unlikely to have pheochromocytoma.

Tuan has pheochromocytoma______________________________________

Therefore, Tuan is unlikely to have hypertension

What do we want to know? • ClinicalP(+ve | Diseased): probability of a +ve test given that the

patient has the disease

P(Diseased | +ve): probability of that the patient has the disease given that he has a +ve test

• ResearchP(Significant test | No association): probability that the test is

significant given that there is no association

P(Association | Significant test): probability that there is an association given that the test statistic is significant

Diagnostic and statistical reasoning

Diagnosis ResearchAbsence of disease There is no real difference

Presence of disease There is a difference

Positive test result Statistical significance

Negative test result Statistical non-significance

Sensitivity (true positive rate) Power (1-)

False positive rate P-value

Prior probability of disease (prevalence)

Prior probability of research hypothesis

Positive predictive value Bayesian probability

For a given sample size, posterior probability increases with p-value

Prior Probability of Association

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Distribution of sample sizes

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Ioannidis et al, Trends Mol Med 2003

Distribution of effect sizes

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Correlation between the odds ratio in the first studies and in subsequent studies

Ioannidis et al, Nat Genet 2001

Evolution of the strength of an association as more information is accumulated Ioannidis et al, Nat Genet 2001

Predictors of statistically significant discrepancies between the first and subsequent studies of the same

genetic association

Predictor Odds ratio – univariate analysis

Odds ratio – multivariate analysis

Total no. of studies (per association)

1.17 (1.03, 1.33) 1.18 (1.02, 1.37)

Sample size of the first study

0.42 (0.17, 0.98) 0.44 (0.19, 0.99)

Single first study with clear genetic effect

9.33 (1.01, 86.3) NS

Ioannidis et al, Nat Genet 2001